Index

_

__call__() (ise.utils.training.CheckpointSaver method) (ise.utils.training.EarlyStoppingCheckpointer method) __getitem__() (ise.data.dataclasses.EmulatorDataset method) (ise.data.dataclasses.PyTorchDataset method) (ise.data.dataclasses.ScenarioDataset method) (ise.data.dataclasses.TSDataset method) __len__() (ise.data.dataclasses.EmulatorDataset method) (ise.data.dataclasses.PyTorchDataset method) (ise.data.dataclasses.ScenarioDataset method) (ise.data.dataclasses.TSDataset method)

_calculate_ivaf_minus_control() (ise.data.process.ProjectionProcessor method) _calculate_ivaf_single_file() (ise.data.process.ProjectionProcessor method) _determine_if_better() (ise.utils.training.CheckpointSaver method) _get_forcing_metadata() (ise.data.process.DatasetMerger method) _including_model_characteristics (ise.data.feature_engineer.FeatureEngineer attribute) _to_tensor() (ise.data.dataclasses.EmulatorDataset method) _update_best_loss() (ise.utils.training.CheckpointSaver method)

A

add_lag_variables() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1] add_model_characteristics() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1]

add_variable_to_nc() (in module ise.utils.functions) aleatoric() (ise.models.density_estimators.normalizing_flow.NormalizingFlow method)

B

backfill_outliers() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1]

base_distribution (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) best_loss (ise.utils.training.CheckpointSaver attribute)

C

calculate_distribution_metrics() (in module ise.utils.functions) calculate_ece() (in module ise.evaluation.metrics) check_input() (in module ise.utils.functions) checkpoint_path (ise.utils.training.CheckpointSaver attribute) CheckpointSaver (class in ise.utils.training) combine_gris_forcings() (in module ise.data.process) combine_testing_results() (in module ise.utils.functions)

component_weights (ise.models.loss.WeightedPCALoss attribute) convert_and_subset_times() (in module ise.data.process) counter (ise.utils.training.EarlyStoppingCheckpointer attribute) create_distribution() (in module ise.utils.functions) criterion (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) (ise.models.predictors.lstm.LSTM attribute) crps() (in module ise.evaluation.metrics) custom_weights (ise.models.loss.WeightedMSEPCALoss attribute)

D

data (ise.data.feature_engineer.FeatureEngineer attribute) data_mean (ise.models.loss.WeightedMSELoss attribute) (ise.models.loss.WeightedMSELossWithSignPenalty attribute) (ise.models.loss.WeightedMSEPCALoss attribute) data_std (ise.models.loss.WeightedMSELoss attribute) (ise.models.loss.WeightedMSELossWithSignPenalty attribute) (ise.models.loss.WeightedMSEPCALoss attribute) DatasetMerger (class in ise.data.process) deep_ensemble (ise.models.ISEFlow.ISEFlow.ISEFlow attribute) DeepEnsemble (class in ise.models.predictors.deep_ensemble)

densities_path (ise.data.process.ProjectionProcessor attribute) device (ise.data.scaler.LogScaler attribute) (ise.data.scaler.RobustScaler attribute) (ise.data.scaler.StandardScaler attribute) (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) (ise.models.ISEFlow.ISEFlow.ISEFlow attribute) (ise.models.loss.WeightedGridLoss attribute) (ise.models.predictors.lstm.LSTM attribute) drop_outliers() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1] dropout (ise.models.predictors.lstm.LSTM attribute)

E

early_stop (ise.utils.training.EarlyStoppingCheckpointer attribute) EarlyStoppingCheckpointer (class in ise.utils.training) EmulatorDataset (class in ise.data.dataclasses) enable_dropout() (ise.models.variational_lstm_emulator.VariationalLSTMEmulator method)

ensemble_members (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) epsilon (ise.data.scaler.LogScaler attribute) evaluate() (ise.models.scenario.ScenarioPredictor method) experiments (ise.data.process.DatasetMerger attribute)

F

FeatureEngineer (class in ise.data.feature_engineer) features (ise.data.dataclasses.ScenarioDataset attribute) fill_mrro_nans() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1] fit() (ise.data.scaler.LogScaler method), [1] (ise.data.scaler.RobustScaler method), [1] (ise.data.scaler.StandardScaler method), [1] (ise.models.density_estimators.normalizing_flow.NormalizingFlow method) (ise.models.ISEFlow.ISEFlow.ISEFlow method) (ise.models.predictors.deep_ensemble.DeepEnsemble method) (ise.models.predictors.lstm.LSTM method) (ise.models.scenario.ScenarioPredictor method) flow (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) flow_hidden_features (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute)

forcing_metadata (ise.data.process.DatasetMerger attribute) forcing_paths (ise.data.process.DatasetMerger attribute) forcings_directory (ise.data.process.ProjectionProcessor attribute) forward() (ise.models.ISEFlow.ISEFlow.ISEFlow method) (ise.models.loss.GridCriterion method) (ise.models.loss.MSEDeviationLoss method) (ise.models.loss.WeightedGridLoss method) (ise.models.loss.WeightedMSELoss method) (ise.models.loss.WeightedMSELossWithSignPenalty method) (ise.models.loss.WeightedMSEPCALoss method) (ise.models.loss.WeightedPCALoss method) (ise.models.predictors.deep_ensemble.DeepEnsemble method) (ise.models.predictors.lstm.LSTM method) (ise.models.scenario.ScenarioPredictor method) (ise.models.variational_lstm_emulator.VariationalLSTMEmulator method)

G

get_all_filepaths() (in module ise.utils.functions) get_data() (in module ise.utils.functions) get_latent() (ise.models.density_estimators.normalizing_flow.NormalizingFlow method) get_model_densities() (in module ise.data.process)

get_uncertainty_bands() (in module ise.utils.functions) get_X_y() (in module ise.utils.functions) get_xarray_data() (in module ise.data.process) GridCriterion (class in ise.models.loss) group_by_run() (in module ise.utils.functions)

I

ice_sheet (ise.data.process.ProjectionProcessor attribute) input_size (ise.models.ISEFlow.de.ISEFlow_AIS_DE attribute) (ise.models.ISEFlow.de.ISEFlow_GrIS_DE attribute) (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) (ise.models.predictors.lstm.LSTM attribute) interpolate_values() (in module ise.data.process) inverse_transform() (ise.data.scaler.LogScaler method), [1] (ise.data.scaler.RobustScaler method), [1] (ise.data.scaler.StandardScaler method), [1] iqr_ (ise.data.scaler.RobustScaler attribute) ise module ise.data.dataclasses module ise.data.feature_engineer module ise.data.process module ise.data.scaler module ise.evaluation.metrics module ise.models.density_estimators.normalizing_flow module ise.models.ISEFlow.de module

ise.models.ISEFlow.ISEFlow module ise.models.ISEFlow.nf module ise.models.loss module ise.models.predictors.deep_ensemble module ise.models.predictors.lstm module ise.models.scenario module ise.models.variational_lstm_emulator module ise.utils.functions module ise.utils.training module ISEFlow (class in ise.models.ISEFlow.ISEFlow) ISEFlow_AIS (class in ise.models.ISEFlow.ISEFlow) ISEFlow_AIS_DE (class in ise.models.ISEFlow.de) iseflow_ais_ensemble (ise.models.ISEFlow.de.ISEFlow_AIS_DE attribute) ISEFlow_AIS_NF (class in ise.models.ISEFlow.nf) ISEFlow_GrIS (class in ise.models.ISEFlow.ISEFlow) ISEFlow_GrIS_DE (class in ise.models.ISEFlow.de) iseflow_gris_ensemble (ise.models.ISEFlow.de.ISEFlow_GrIS_DE attribute) ISEFlow_GrIS_NF (class in ise.models.ISEFlow.nf)

J

js_divergence() (in module ise.evaluation.metrics)

K

kl_divergence() (in module ise.evaluation.metrics)

kolmogorov_smirnov() (in module ise.evaluation.metrics)

L

labels (ise.data.dataclasses.ScenarioDataset attribute) linear1 (ise.models.predictors.lstm.LSTM attribute) linear_out (ise.models.predictors.lstm.LSTM attribute) load() (ise.data.scaler.LogScaler method) (ise.data.scaler.LogScaler static method) (ise.data.scaler.RobustScaler method) (ise.data.scaler.RobustScaler static method) (ise.data.scaler.StandardScaler method) (ise.data.scaler.StandardScaler static method) (ise.models.density_estimators.normalizing_flow.NormalizingFlow static method) (ise.models.ISEFlow.ISEFlow.ISEFlow static method) (ise.models.ISEFlow.ISEFlow.ISEFlow_AIS static method) (ise.models.ISEFlow.ISEFlow.ISEFlow_GrIS static method) (ise.models.predictors.deep_ensemble.DeepEnsemble class method) (ise.models.scenario.ScenarioPredictor method)

load_checkpoint() (ise.utils.training.CheckpointSaver method), [1] load_ml_data() (in module ise.utils.functions) load_model() (in module ise.utils.functions) log (ise.utils.training.CheckpointSaver attribute) LogScaler (class in ise.data.scaler) loss_choices (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) LSTM (class in ise.models.predictors.lstm) lstm (ise.models.predictors.lstm.LSTM attribute) lstm_num_hidden (ise.models.predictors.lstm.LSTM attribute) lstm_num_layers (ise.models.predictors.lstm.LSTM attribute)

M

mape() (in module ise.evaluation.metrics) mean_ (ise.data.scaler.StandardScaler attribute) mean_absolute_error() (in module ise.evaluation.metrics) mean_squared_error() (in module ise.evaluation.metrics) mean_squared_error_sector() (in module ise.evaluation.metrics) median_ (ise.data.scaler.RobustScaler attribute) merge_dataset() (ise.data.process.DatasetMerger method), [1] merge_datasets() (in module ise.data.process) merge_sectors() (ise.data.process.DatasetMerger method), [1] min_value (ise.data.scaler.LogScaler attribute) model (ise.utils.training.CheckpointSaver attribute) module ise ise.data.dataclasses ise.data.feature_engineer ise.data.process ise.data.scaler ise.evaluation.metrics ise.models.density_estimators.normalizing_flow ise.models.ISEFlow.de ise.models.ISEFlow.ISEFlow ise.models.ISEFlow.nf ise.models.loss ise.models.predictors.deep_ensemble ise.models.predictors.lstm ise.models.scenario ise.models.variational_lstm_emulator ise.utils.functions ise.utils.training

MSEDeviationLoss (class in ise.models.loss)

N

normalizing_flow (ise.models.ISEFlow.ISEFlow.ISEFlow attribute) NormalizingFlow (class in ise.models.density_estimators.normalizing_flow) num_features (ise.data.dataclasses.EmulatorDataset attribute) num_flow_transforms (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute)

num_input_features (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) num_predicted_sle (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) num_projections (ise.data.dataclasses.EmulatorDataset attribute) num_timesteps (ise.data.dataclasses.EmulatorDataset attribute)

O

optimizer (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) (ise.models.predictors.lstm.LSTM attribute) (ise.utils.training.CheckpointSaver attribute) output_directory (ise.data.feature_engineer.FeatureEngineer attribute) output_sequence_length (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) (ise.models.predictors.lstm.LSTM attribute)

output_size (ise.models.ISEFlow.de.ISEFlow_AIS_DE attribute) (ise.models.ISEFlow.de.ISEFlow_GrIS_DE attribute) (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) (ise.models.predictors.lstm.LSTM attribute)

P

patience (ise.utils.training.EarlyStoppingCheckpointer attribute) penalty_multiplier (ise.models.loss.MSEDeviationLoss attribute) predict() (ise.models.ISEFlow.ISEFlow.ISEFlow method) (ise.models.ISEFlow.ISEFlow.ISEFlow_AIS method) (ise.models.predictors.deep_ensemble.DeepEnsemble method) (ise.models.predictors.lstm.LSTM method) (ise.models.scenario.ScenarioPredictor method) (ise.models.variational_lstm_emulator.VariationalLSTMEmulator method) process() (ise.data.process.ProjectionProcessor method), [1] (ise.models.ISEFlow.ISEFlow.ISEFlow_AIS method)

process_AIS_atmospheric_sectors() (in module ise.data.process) process_AIS_oceanic_sectors() (in module ise.data.process) process_AIS_outputs() (in module ise.data.process) process_GrIS_atmospheric_sectors() (in module ise.data.process) process_GrIS_oceanic_sectors() (in module ise.data.process) process_GrIS_outputs() (in module ise.data.process) process_sectors() (in module ise.data.process) projection_paths (ise.data.process.DatasetMerger attribute) ProjectionProcessor (class in ise.data.process) projections_directory (ise.data.process.ProjectionProcessor attribute) PyTorchDataset (class in ise.data.dataclasses)

R

r2_score() (in module ise.evaluation.metrics) reduction (ise.models.loss.WeightedPCALoss attribute) relative_squared_error() (in module ise.evaluation.metrics)

relu (ise.models.predictors.lstm.LSTM attribute) resolution (ise.data.process.ProjectionProcessor attribute) RobustScaler (class in ise.data.scaler)

S

sample() (ise.models.density_estimators.normalizing_flow.NormalizingFlow method) save() (ise.data.scaler.LogScaler method), [1] (ise.data.scaler.RobustScaler method), [1] (ise.data.scaler.StandardScaler method), [1] (ise.models.density_estimators.normalizing_flow.NormalizingFlow method) (ise.models.ISEFlow.ISEFlow.ISEFlow method) (ise.models.predictors.deep_ensemble.DeepEnsemble method) save_checkpoint() (ise.utils.training.CheckpointSaver method), [1] scale_ (ise.data.scaler.StandardScaler attribute) scale_data() (in module ise.data.feature_engineer) (ise.data.feature_engineer.FeatureEngineer method), [1] scalefac_path (ise.data.process.ProjectionProcessor attribute) scaler_path (ise.models.ISEFlow.ISEFlow.ISEFlow attribute)

scaler_X (ise.data.feature_engineer.FeatureEngineer attribute) scaler_X_path (ise.data.feature_engineer.FeatureEngineer attribute) scaler_y (ise.data.feature_engineer.FeatureEngineer attribute) scaler_y_path (ise.data.feature_engineer.FeatureEngineer attribute) ScenarioDataset (class in ise.data.dataclasses) ScenarioPredictor (class in ise.models.scenario) sequence_length (ise.data.dataclasses.EmulatorDataset attribute) (ise.data.dataclasses.TSDataset attribute) sign_penalty_factor (ise.models.loss.WeightedMSELossWithSignPenalty attribute) split_data() (ise.data.feature_engineer.FeatureEngineer method), [1] split_training_data() (in module ise.data.feature_engineer) StandardScaler (class in ise.data.scaler) sum_by_sector() (in module ise.evaluation.metrics)

T

t (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) t_test() (in module ise.evaluation.metrics) test (ise.data.feature_engineer.FeatureEngineer attribute) test_size (ise.data.feature_engineer.FeatureEngineer attribute) threshold (ise.models.loss.MSEDeviationLoss attribute) to_tensor() (in module ise.utils.functions) total_variation_regularization() (ise.models.loss.GridCriterion method) (ise.models.loss.WeightedGridLoss method) train (ise.data.feature_engineer.FeatureEngineer attribute)

train_size (ise.data.feature_engineer.FeatureEngineer attribute) trained (ise.models.density_estimators.normalizing_flow.NormalizingFlow attribute) (ise.models.ISEFlow.ISEFlow.ISEFlow attribute) (ise.models.predictors.deep_ensemble.DeepEnsemble attribute) (ise.models.predictors.lstm.LSTM attribute) transform() (ise.data.scaler.LogScaler method), [1] (ise.data.scaler.RobustScaler method), [1] (ise.data.scaler.StandardScaler method), [1] TSDataset (class in ise.data.dataclasses)

U

undummify() (in module ise.utils.functions) unscale() (in module ise.utils.functions)

unscale_column() (in module ise.utils.functions) unscale_data() (ise.data.feature_engineer.FeatureEngineer method), [1]

V

val (ise.data.feature_engineer.FeatureEngineer attribute) val_size (ise.data.feature_engineer.FeatureEngineer attribute)

VariationalLSTMEmulator (class in ise.models.variational_lstm_emulator) verbose (ise.utils.training.CheckpointSaver attribute)

W

weight_factor (ise.models.loss.WeightedMSELoss attribute) (ise.models.loss.WeightedMSELossWithSignPenalty attribute) (ise.models.loss.WeightedMSEPCALoss attribute) weighted_pixelwise_mse() (ise.models.loss.WeightedGridLoss method)

WeightedGridLoss (class in ise.models.loss) WeightedMSELoss (class in ise.models.loss) WeightedMSELossWithSignPenalty (class in ise.models.loss) WeightedMSEPCALoss (class in ise.models.loss) WeightedPCALoss (class in ise.models.loss)

X

X (ise.data.dataclasses.EmulatorDataset attribute) (ise.data.dataclasses.TSDataset attribute)

xdim (ise.data.dataclasses.EmulatorDataset attribute)

Y

y (ise.data.dataclasses.EmulatorDataset attribute) (ise.data.dataclasses.TSDataset attribute)